Not zero! But also far from 100%.
I suppose one thing that’s convenient about short-form blogging (like what I do here) is how the question doesn’t even really arise because doing all your writing yourself is only just as much work as coming up with a prompt for an AI to write the same thing.
Matthias
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Jobs we love
A long time ago I read a blurb in some magazine that argued that sure, you could select a subject you actually enjoy when choosing your university major or your career or whatever, but what you really want to do is choose something that maximizes your income, the reasoning being that money tends to be useful. At the time, being an idealistic youth who did not have or particularly feel the need for money, I did not find that reasoning very compelling, so I went ahead and ignored it and chose computer science for my major.
That turned out not to be the worst possible choice money-wise because the market situation at the time of my graduation happened to be just right and I found a nice, rent-paying job rather quickly. And to this day I struggle with the picture in my head of this blurb in the magazine that tried to convince me to go into finance or management or health care or something. Would it have ruined my life? Or would I now be a multi-millionaire who owns a bunch of nice homes with impressive backyards? Who knows!
And if I think of the people who this blurb supposedly actually addressed – those who were thinking of entering fields with names like Bashkirology or Deconstructive Sociology or Physics – many of those people seem… fine? A lot of them have grudgingly accepted jobs that pay them money and those jobs have turned out not be so bad after all. Others have married well-off engineers or doctors, so their nominal incomes don’t bother them very much, and maybe they have since divorced and got to keep a good amount of money for themselves. Most seem to be living in nice homes, some of which with impressive backyards. So their strategy can’t have been all that bad!
Law school is just for fun
I was reminded of this when I attended a summer school on Japanese law in the spring. The professor who was leading the event asked me what I was doing there in my something-other-than-a-law-student capacity. When I replied that I was just there for fun, he asked why I wasn’t considering law school. I found it very flattering that he would ask me that at my age, but it did leave me wondering: I suppose you could just switch fields completely in your 40s. Should you? What if that means going from a higher-paying profession to a lower-paying one? How dumb (or financially safe) would you have to be to decide to do so? (Also: Would it still be fun if you received money for it? It isn’t obvious!)
Indeed, what about downgrading your career in other ways? Say you are a Most Distinguished Principal Engineer, but really prefer to be a Just Highly Distinguished Foot Soldier Engineer? Should you?
Will you be happier with your job? Does it mean you now have to go look for a wealthy engineer or doctor to marry?
Annoyingly, I nowadays find myself forced to admit that the blurb in the magazine had a point. Money sure is useful. Having enough of it gives you lots of life options. You can marry someone poor! You can buy a house! You can get a babysitter and play video games all day! It’s nice! Maybe hating your job isn’t so bad after all!
Maybe at least aim for the middle. And then wait until the Era of AI comes around in a few years and jobs are a thing of the past. Then you can ignore what the annoying magazines say.
Another sandbox for AI agents.
Shows you your coding agent usage stats.
You don’t say.
A Python–C++ binding helper library.
Advanced general-purpose physics simulation library with both C and C++ APIs. Also has official Python bindings.
Another sandbox for AI agents. By NVIDIA.
“Breakthrough Method for Agile AI-Driven Development.” I have no idea what it is, but it sounds cool.
A game engine for Common Lisp.
Ruby for microcontrollers.
In AI, whatever scales with compute wins. Human preconceptions are one example of what always loses out in the long run.
This is because our human way of thinking rests on simplifications and abstractions, both of which progressively lose value the more compute you have.
Matthias
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Is the “spec-driven development” trend a failure in heeding the Bitter Lesson? Or is it a practical temporary crutch until example-driven development becomes the norm?
The Bitter Lesson: In AI, whatever scales with compute wins. Human preconceptions are one example of what does not scale well.
Many AI agent harnesses get this wrong and encode their human creators’ ideas about workflows too strongly.
Reddit for AI agents (as opposed to for humans).
A Gerbil Scheme REPL MCP server for coding agents.
REPL-driven workflows have been agent-unfriendly so far, so I welcome this. Personally I would have implemented a Claude Code skill instead of an MCP server, but as long as it works…
A sandboxing tool for macOS (sandbox_exec) and GNU/Linux (Bubblewrap).
Restricts:
- Filesystem. The heart of every sandboxing solution.
- Network. Forces outbound connections through a SOCKS or HTTP proxy, which enables fine-grained control.
- Commands. Not sure how this works; regardless, I am skeptical of this one. After all, what does it help to catch a shell command when the sandboxed application can just implement the same behavior directly?
I like the network part. In fact I explored the possibility of this kind of sandboxing combined with HTTP proxying just a week ago; Claude also suggested using Bubblewrap, which matches. I did not think of SOCKS proxying for non-HTTP connections, so I’m glad I found this.
That said, I think the HTTP proxying part here falls a bit short of my ideal solution, which would try harder to prevent data extrusion.
Nomos-Verlag, 978-3-8487-7897-3.